Systems and methods for spectral authentication of a feature of a document

ABSTRACT

Systems and methods for authenticating a document are provided. In one embodiment, a method for authenticating a feature of a document includes capturing a first image of a region of a document while the region is subjected to a first wavelength of electromagnetic radiation. The region includes at least a portion of the document. The method also includes determining a first intensity value associated with the first image of the region, and comparing the first intensity value with a first training intensity value of a region of a training document. The first training intensity value is obtained using the first wavelength of electromagnetic radiation. The method also includes determining whether the document is authentic at least partially based on the comparison between the first intensity value and the first training intensity value.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present application is a continuation of U.S. patent applicationSer. No. 13/563,612 filed Jul. 31, 2012, (now U.S. Pat. No. 9,053,596)entitled “Systems and Methods for Spectral Authentication of a Featureof a Document,” which is hereby incorporated herein by reference for allpurposes.

TECHNICAL FIELD

The illustrative embodiments relate generally to documentauthentication, and more particularly, to systems and methods forspectral authentication of a feature of a document.

BACKGROUND

The rise in technology has led to greater sophistication in the field ofdocument authentication. Document features, such as inks, holograms,vignette windows, security threads, etc., are being increasingly used todecrease the likelihood of counterfeiting. For example, special inks,which may be applied to currently, may have a unique spectral profilethat is difficult to mimic without access to sophisticated knowledge andtechnology, thereby decreasing the likelihood of counterfeiters copyingand applying these inks to counterfeit currency. As documentauthentication features have become more sophisticated, a need hasarisen for new methods of authenticating these and other features.

SUMMARY

According to an illustrative embodiment, a method for authenticating afeature of a document includes capturing a first image of a region of adocument while the region is subjected to a first wavelength ofelectromagnetic radiation. The region includes at least a portion of thedocument. The method also includes determining a first intensity valueassociated with the first image of the region, and comparing the firstintensity value with a first training intensity value of a region of oneor more training documents. The first training intensity value isobtained using the first wavelength of electromagnetic radiation. Themethod also includes determining whether the document is authentic atleast partially based on the comparison, between the first intensityvalue and the first training intensity value.

According to another embodiment, a method for authenticating a featureof a document includes determining a spectral profile of a region of adocument in a predetermined electromagnetic radiation range using two ormore images of the region. The region includes at least a portion of thedocument. Each of the two or more images are captured while the regionis subjected to one of a plurality of wavelengths of electromagneticradiation in the predetermined electromagnetic radiation range. Themethod also includes comparing the spectral profile of the region of thedocument to a training spectral profile of a region of one or moretraining documents, and determining whether the documents authenticbased on the comparison between the spectral profile and the trainingspectral profile.

According to another embodiment, a system for authenticating a featureof a document includes an image sensor to capture a first image of aregion of a document while the region is subjected to a first wavelengthof electromagnetic radiation. The image sensor to further capture asecond image of the region of the document while the region is subjectedto a second wavelength of electromagnetic radiation. The region includesat least a portion of the document. The system also includes anintensity value determination module, at least partially implemented bya processor, to determine a first intensity value associated with thefirst image of the region. The intensity value determination modulefurther determines a second intensity value associated with the secondimage of the region. The system also includes a comparison module, atleast partially implemented by the processor, to compare the firstintensity value with a first training intensity value of a region of atraining document. The first training intensity value is obtained usingthe first wavelength of electromagnetic radiation. The comparison modulefurther compares the second intensity value with a second trainingintensity value of the region of the training document. The secondtraining intensity value is obtained using the second wavelength ofelectromagnetic radiation. The system further includes an authenticationmodule to determine whether the document is authentic at least partiallybased on the comparison between the first intensity value and the firsttraining intensity value and at least partially based on the comparisonbetween the second intensity value and the second training intensityvalue.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a schematic, pictorial representation of a method forauthenticating a feature of a document according to an illustrativeembodiment;

FIG. 2 is a schematic, block diagram of a document authentication systemaccording to an illustrative embodiment;

FIG. 3 is a graph showing a spectral profile of a region of a documentaccording to one illustrative embodiment;

FIG. 4 is a histogram of pixel intensity versus percent of pixels usedin one illustrative embodiment;

FIG. 5 is s a schematic, pictorial representation of a system forcapturing one or more images of a document according to an illustrativeembodiment;

FIGS. 6A and 6B schematic, pictorial representations of how the one ormore images are formed using the system of FIG. 5A according to anillustrative embodiment;

FIG. 7 is a schematic, pictorial representation of a system forcapturing one or more images of a document according to an illustrativeembodiment;

FIG. 8 is a flowchart of a process for authenticating a feature of adocument according to an illustrative embodiment;

FIG. 9 is a flowchart of another process for authenticating a feature ofa document according to an illustrative embodiment;

FIG. 10 is a flowchart of a process for determining a respectiveintensity value for each of the plurality of images and for determiningwhether a document is authentic according to an illustrative embodiment;

FIG. 11 is a flowchart of another process for authenticating a featureof a document according to an illustrative embodiment; and

FIG. 12 is a schematic, block diagram of a data processing system inwhich the illustrative embodiments may be implemented.

DETAILED DESCRIPTION

In the following detailed description of the illustrative embodiments,reference is made to the accompanying drawings that form a part hereof.These embodiments are described in sufficient detail to enable thoseskilled in the art to practice the invention, and it is understood thatother embodiments may be utilized and that logical structural,mechanical, electrical, and chemical changes may be made withoutdeparting from the spirit or scope of the invention. To avoid detail notnecessary to enable those skilled in the art to practice the embodimentsdescribed herein, the description may omit certain information known tothose skilled in the art. The following detailed description is,therefore, not to be taken in limiting sense, and the scope of theillustrative embodiments are defined only by the appended claims.

Referring to FIGS. 1 through 4, an illustrative embodiment of a documentauthentication system 100 includes one or more light sources 102 and oneor more image sensors 104 controlled by an image capturing module 106,which is part of a document authentication application 108, to captureone or more images 110, 112 of a region 114 of a document 116. In oneexample, the document 116 may be a banknote from any country of origin.Other types of documents 116 with which the document authenticationsystem 100 may be used include financial documents (e.g., checks, moneyorders, travelers checks, etc.), legal-related documents, passports, orany other type of document. Unless otherwise indicated, as used herein,“or” does not require mutual exclusivity. The region 114 may include allor any portion of the document 116. Each of the images 110, 112 capturedby the image capturing module 106 may be captured while the region 114is at least partially subjected to different wavelengths ofelectromagnetic radiation. For example, the image 110 may be captured bythe image sensor 104 while the light source 102 subjects the region 114to a first wavelength in the electromagnetic spectrum. Further, theimage sensor 104 may capture the image 112 while the light source 102subjects the region 114 to a second wavelength that is different fromthe first wavelength. In this manner, the image capturing module 106 maycapture any number of images of the region 114 at different wavelengthsin the electromagnetic spectrum. In another embodiment, a portion of theimages captured by the image capturing module 106 may be captured at thesame wavelength.

The document authentication application 108 may include an imageanalysis module 118 that analyzes or processes the images 110, 112captured by the image capturing module 106. The image analysis module118 may include an intensity value determination module 120 thatdetermines an intensity value 122, 124 for each of the images 110, 112,respectively. The intensity values 122, 124 may be any value indicativeof the intensity or reflectivity of all or a portion of the images 110,112, respectively. In one embodiment, the intensity values 122, 124 maybe the mean intensity values of the pixels of each image 110, 112,respectively. However, other values, such as the median, maximum,minimum, average, etc., indicative of or associated with the intensityof the pixels may be used for the intensity values 122, 124.

Referring to FIG. 3, an example spectral profile 125 of the region 114of the document 116 is shown. The spectral profile 125 is plotted on agraph of reflectivity, or intensity, versus wavelength. The wavelengthincludes both the visible and infrared range, although any range in theelectromagnetic spectrum may be used for the spectral profile 125. Thespectral profile 125 shows that the reflectance of the region 114 variesover wavelength. In the particular example of the region 114, thespectral profile 125 sharply drops in the visible range and begins tolevel off in and through the infrared range. The data points of thespectral profile 125 include the intensity values 122, 124 that aredetermined by the intensity value determination module 120, as shown inFIG. 3. As the number of images of the region 114 is increased, thespectral profile 125 of the region 114 may be determined at higherresolutions since each image, and in particular each image's intensityvalue, constitutes a data point of the spectral profile 125. Therefore,in embodiment, several images may be captured of the region 114, each atdifferent wavelengths, in order to better approximate the spectralprofile 125 of the region 114. As will be discussed in further detailbelow, the spectral profile 125 may then be compared to a trainingspectral profile from one or more known authentic documents to determinewhether the region 114, and therefore the document 116, has beencounterfeited, deteriorated, or been damaged.

The document authentication application 108 includes a comparison module126 that compares the intensity values (e.g., mean intensity values)122, 124 with corresponding training intensity values 128, 130. Thecomparison module 126 may employ any suitable means for comparing themeasured data to training data. Non-limiting illustrative examples ofcomparative operations that may be employed by the comparison module 126include difference, weighted difference, correlation to determine adegree of similarity (or difference) between a measured spectral profileand a training spectral profile, statistical difference, threshold test(s), or any other suitable computation.

The training intensity values 128, 130 may be obtained from at least onetraining document 132 that is used as a benchmark or model to determinewhether the document 116 is authentic. For example, the trainingdocument 132 may be a particular type of currency that is known to beauthentic, such as currency produced by an authorized, orgovernment-sanctioned source. A training module 133 may capture one ormore images 134, 136 of a training region 138 of the training document132 in conjunction with the image capturing module 106, the light source102, and the image sensor 104. In another embodiment, the trainingmodule 133 may be separate from the document authentication application108 and be implemented by a different device, authority, or entity thanthat used to process and authorize the document 116. The training images134, 136 may undergo processing to determine the training intensityvalues 123, 130 for each of the training images 130, 136, respectively.To provide comparisons between wavelength-dependent intensities of thetraining document 132 and the document 116, the images 110, 112 may becaptured at the same or similar wavelengths as the training images 134,136 of the training document 132. In the example of FIG. 1, both of theimages 110 and 134 are captured at a first wavelength, and the images112 and 136 are captured at a second wavelength. The number of imagescaptured of each the document 116 and the training document 132 may bemore than two (e p. 8, 15, 100, 1000, etc.) and these images maycorrespond by wavelength to another in a similar manner. Also, in oneembodiment, training data may be collected from a plurality of trainingdocuments, whereby an average or acceptable range may be determined forcomparison with the images 110, 112.

The training intensity value 128 is indicative of an intensity of theimage 134 and the training intensity value 130 is indicative of anintensity of the image 136. In one embodiment, the training intensityvalues 128, 130 may include a mean training intensity and a standarddeviation of the mean training intensity for the images 134 and 136,respectively. However, other values, such as the median, maximum,minimum, average, etc., indicative of or associated with the intensityof the pixels may be used for the training intensity values 128, 130.

Similar to the spectral profile 125 described above, the trainingintensity values 128. 130 may be used to determine a training spectralprofile for the training region 138 of the training document. 132. Thespectral profile 125 may be compared to the training spectral profile(not shown) to determine whether the document 116 is authentic. Thecomparison may employ any suitable means for comparing the measured datato training data. Non-limiting illustrative examples of comparativeoperations that may be employed include difference, weighted difference,correlation to determine a degree of similarity (or difference) betweena measured spectral profile and a training spectral statisticaldifference, threshold test(s), or any other suitable computation. In oneembodiment, the closer the spectral profile 125 of the document 116matches the training spectral profile of the training document 132, themore likely it is that the document 116 is authentic, and thresholds maybe used to determine how closely the spectral profile 125 must match thetraining spectral profile for the document 116 to be judged authentic.By using such a comparison between spectral profiles, special, or hardto reproduce, inks may be used on documents, such as currency, toprevent counterfeiters from easily copying features using those inks. Inthe example of FIG. 3, the spectral profile 140 is shown in dotted linesto illustrate a typical ink that has sometimes been used on currency; asindicated by the spectral profile 140, the ink has a simpler profile,and may therefore be easier to reproduce by counterfeiters. The spectralprofile 125 of the region 114 is slightly more complex, and allows forgreater likelihood that a counterfeit ink might be prevented. However,it will be appreciated that the illustrative embodiments may be used todetermine the authenticity of inks having either simple or complexspectral profiles.

In one embodiment, the comparison module 126 may compare pairs ofcorresponding intensity values and training intensity values that arecaptured using the same wavelength. For example, the intensity value 122may be compared to the training intensity value 128 since they are bothcaptured using the first wavelength. Similarly, the intensity value 124may be compared to the training intensity value 130 since they areobtained using the second wavelength. As more images are captured forthe document 116 and the training document 132, more pairs of intensityvalues may be compared across a desired electromagnetic spectrum. In oneembodiment, each intensity value 122, 124 is a mean intensity value, andeach training intensity value 128, 130 includes both a mean trainingintensity value and a standard deviation of the mean training intensityvalue. In this example, for each of the images 110, 112, the comparisonmodule 126 may determine the number of standard deviations the meanintensity value differs from the mean training intensity value. Forexample, the comparison module 126 may determine the number of standarddeviations the mean intensity value 122 differs from the mean trainingintensity value 128. Similarly, the comparison module 126 may determinethe number of standard deviations that the mean intensity value 124differs from the mean training intensity value 130. In one embodiment,more than one training document may be used, and the standard deviationused by the comparison module may be computed over a number of trainingdocuments. The comparison may employ any suitable means for comparingthe measured data to training data. Non-limiting illustrative examplesof comparative operations that may be employed include difference,weighted difference, correlation to determine a degree of similarity (ordifference) between a measured spectral profile and a training spectralprofile, statistical difference, threshold test(s), or any othersuitable computation.

Based on the comparison between the mean intensity values 122, 124 withthe mean training intensity values 128, 130, respectively, anauthentication module 142 may determine whether the document 116 isauthentic. In one embodiment, the authentication module 142 maydetermine an average deviation between the mean intensity values 122,124 and the mean training intensity values 128, 130. In particular, theauthentication module 142 may use the training standard deviation of thetraining image 134 to determine a number of training standard deviationsthat the mean intensity value 122 differs from the mean trainingintensity value 128. Similarly, the training standard deviation of thetraining image 136 may he used to determine a number of trainingstandard deviations the mean intensity value 124 differs from the meanthe training intensity value 130. After taking standard deviationmeasurements for each pair of images as described above, theauthentication module 142 may determine an average deviation. If theaverage deviation meets or exceeds a predetermined threshold, thedocument 116 may be determined to not be authentic. Conversely, if theaverage deviation is equal to or less than the predetermined threshold,the document 116 may be determined to be authentic. In anotherembodiment, the average deviation may be a weighted average.

In yet another embodiment, the authentication module 142 may determinethe largest deviation between each corresponding pair of intensityvalues 122, 124 and training intensity values 128, 130. Specifically,the deviation may be determined between the mean intensity value 122 andthe mean training intensity value 128, the mean intensity value 124 andthe mean training intensity value 130, and so on for any additionalpairs of images. The authentication module 142 may then determinelargest deviation (e.g., most number of standard deviations) betweencorresponding pairs of intensity values. If the largest deviation meetsor exceeds a predetermined threshold, the document 116 may be determinedto be not authentic. Conversely, if the largest deviation is equal orless than the predetermined threshold, the document 116 may bedetermined, to be authentic.

In one embodiment, using a pixel targeting module 143, a portion of thepixels of each image 110, 112 may be selected to determine respectiveintensity values 122, 124. Selecting which pixels to be used incalculating an intensity value may help to reduce or eliminate outlyingdata, such as pixels that are not part of a target feature, whendetermining the intensity value. In one example, a histogram 144 may begenerated for each of the images 110, 112. FIG. 4 shows the histogram144 for the image 110. The histogram 144 plots pixel intensity versuspercent of pixels for the image 110. The portion of pixels in the image110 that are used to determine the intensity value 122 may be selectedusing the histogram 144. As shown in FIG. 4, the dotted line indicates40% of the pixels of the image 110 have a pixel intensity of “x” orlower. Here, “x” is a generalized representation used to show any pointbetween the minimum and maximum pixel intensity. Any scale of pixelintensity may be used (e.g., 0 to 255, 0 to 100, etc.). In selecting the40% of pixels of the image 110 having a pixel intensity of x or lower,only that chosen 40% is used to determine the intensity value 122 (e.g.,mean intensity value). In another example, the middle 10%, 20%, 30%,40%, 50%, etc. of pixels may be selected to determine the intensityvalue 122 to eliminate the darkest and brightest pixels in the image110. Also, the brightest pixels in the image 110 may be selected usingthe histogram (e.g., brightest 10%, 20%, 30%, 40%, 50%, etc.). Ahistogram such as histogram 144 may be generated for any or all of theimages 110, 112 of the region 114 so that pixel portions may beallocated differently for each wavelength. In one example, the histogram144 may be an integrated transposed histogram.

The document authentication application 108 may also include anormalization module 146 to normalize all or a portion of the intensityvalues 122, 124, 128, 130. In one example, the intensity values 122 and124, such as mean intensity values, may be normalized by selecting oneof the intensity values 122 or 124 and dividing each of the intensityvalues 122, 124 by the selected intensity value. For example, theintensity value 122 may be selected as a normalization value, and boththe intensity value 122 and the intensity value 124 may be divided bythe intensity value 122. Such manner of normalization may occur for anynumber of intensity values for the region 114. The training intensityvalues 128, 130 may also be normalized. The comparison between theintensity values 122, 124 and the training intensity values 128, 130 mayoccur after these intensity values have been normalized. The comparisonmay employ any suitable means for comparing the measured data totraining data. Non-limiting illustrative examples of comparativeoperations that may be employed include difference, weighted difference,correlation to determine a degree of similarity (or difference) betweena measured spectral profile and a training spectral profile, statisticaldifference, threshold, test(s), or any other suitable computation. Inanother embodiment, normalization may occur as the images 110, 112 arecaptured instead of after the intensity values 122, 124 are determined.

As mentioned above, any number of images, such as the images 110 and112, may be captured for the region 114 of the document 116, and each ofthese images may be compared to wavelength-corresponding training imagesof the training region 138 of the training document 132. By way ofnon-limiting example, a total of eight images may be captured for theregion 114, with each of the images captured at the following respectivewavelengths: red, green, blue, infrared wavelength 1, infraredwavelength 2, infrared wavelength 3, infrared wavelength 4, and infraredwavelength 5. Such wavelengths may be useful when verifying orauthenticating an infrared ink that has a unique or characteristicspectral profile 125 in the visible and infrared electromagnetic range.It will be appreciated, however, that the images may be taken anywherealong the electromagnetic spectrum (e.g., gamma, ultraviolet, visible,infrared, etc.) and any number of such images may be taken forcomparison with corresponding training images. The comparison may employany suitable means for comparing the measured data to training data.Non-limiting illustrative examples of comparative operations that may beemployed include difference, weighted difference, correlation todetermine a degree of similarity (or difference) between a measuredspectral profile and a training spectral profile, statisticaldifference, threshold test (s), or any other suitable computation.

In an alternative embodiment, in lieu of or in addition to comparing theintensity values 122, 124 to the training intensity values 128, 130, a“hue” may be calculated using the images 110, 112 over a predeterminedwavelength range, and this hue may be compared to a correspondingtraining hue of the training images 134, 136 taken over substantiallythe same wavelength range. By way of non-limiting example, if red,green, and blue images are captured of the region 114, a hue may becalculated based on these images; a similarly calculated hue of thetraining region 138 may be compared to the hue calculated for the region114 to determine whether the document 116 is authentic. However, it willbe appreciated that the “hue” is not limited to being calculated in thevisible range. For example, in the case that two or more images arecaptured of the region 114 in the infrared range, the infrared hue maybe determined using these images in a similar fashion as would be donein the visible range, and then compared to a corresponding infrared hueof the training region 138 to determine document authenticity. Indeed,in this embodiment a hue may be computed in the visible range,nonvisible range, or any combination of wavelengths in the visible andnonvisible range. In this embodiment, the comparison may employ anysuitable means for comparing the measured data to training data.Non-limiting illustrative examples of comparative operations that may beemployed include difference, weighted difference, correlation todetermine a degree of similarity (or difference) between a measuredspectral profile and a training spectral profile, statisticaldifference, threshold test (s), or any other suitable computation.

Any number of light sources, of any type, may be used in the documentauthentication system 100. The light sources 102 may emit any type ofelectromagnetic radiation (e.g., ultraviolet, infrared, white, red,green, blue, X-ray, ect.) or other suitable electromagnetic radiation.The specific technique or components used to emit electromagneticradiation from the light sources 102 may vary, and may includelight-emitting diodes (LEDs), light bulbs, etc.

Any suitable image sensor 104 capable of capturing any suitable image(frame, line, or otherwise) of a document may be employed and remainwithin the scope of the present disclosure. For example, and withoutlimitation, the image sensor 104 may be a TDI camera, a line scancamera, a frame camera, an x-ray imaging device, one or morephotodiodes, etc.

Referring to FIGS. 5, 6A, and 6B, an illustrative embodiment of a systemand method for capturing images of a region 214 of a document 216includes one or more light sources 202 a, 202 b and the image sensor204. Elements of FIGS. 5, 6A, and 6B that are analogous to elements inFIGS. 1-4 have been shown by indexing the reference numerals by 100. Inthe non-limiting example of FIGS. 6A and 6B, three images 210, 212, 213are captured for the region 214 of the document 216. In particular, afirst plurality of line images 252, 253 may be captured of the region214 while the region is at least partially subjected to a firstwavelength of electromagnetic radiation from one of the light, sources202 a, 202 b. A second plurality of line images 254, 255, 256 may becaptured of the region 214 while the region 214 is at least partiallysubjected to a second wavelength of electromagnetic radiation. A thirdplurality of line images 257, 258, 259 may also be captured by the imagesensor 204 while the region 214 is at least partially subjected to athird wavelength of electromagnetic radiation. Such a sequence of lineimages may be captured by the image sensor 204 across all or a portionof the region 214; FIG. 6A shows line images captured for a portion ofthe region 214 for purposes of illustration. Also, while the linesimages 252-259 are shown in FIG. 6A as non-overlapping, in anotherembodiment all or a portion of the lines images 252-259 may overlap withone another.

The first, second, and third pluralities of line images may then beassembled into respective images 210, 212, 213 of the region 214. Inparticular, the line images 252 and 253, as well as any other lineimages captured at the first wavelength, may be assembled into the image210, the line images 254, 255, 256, as well, as any other line imagescaptured at the second wavelength, may be assembled into the image 212,and the line images 257, 258, 259, as well as any other line imagescaptured at the third wavelength, may be assembled into the image 213.

In the particular case of the embodiment described in FIGS. 5, 6A, and6B, the image sensor 204 may be a line scan camera to facilitatecapturing of each of the line images. Any other arrangement capable ofcapturing line images may also be used (e.g., one or more photodiodes).It will be appreciated that the document 216 may move relative to thelight sources 202 a, 202 b and the image sensor 204. Movement betweenthe document 216, on the one hand, and the light sources 202 a, 202 band the image sensor 204, on the other hand, may be due to relativemovement of any of these elements. For example, the document 216 may bemoved past the line of sights of the light sources 202 a, 202 b and theimage sensor 204 by a roller belt or other means.

In one embodiment, the use of time division multiplexing (TDM) of thedifferent light sources 202 a, 202 b, or other illumination techniquessuch as direct sequence spread spectrum modulation (DSSSM), amulti-spectral array of images spanning multiple detector spectralranges may be formed. The use of additional lines of illumination andarrays of detectors may also be used to further extend the spectralrange.

It will also be appreciated that the plurality of line images may becaptured in a predetermined sequence of illumination. Also, any numberof wavelengths may be utilized to form any number of line images andrespective images formed therefrom, including the example provided abovein which eight wavelengths (red, green, blue, infrared wavelength 1,infrared wavelength 2, infrared wavelength 3, infrared wavelength 4, andinfrared wavelength 5) were used.

Referring to FIG. 7, another illustrative embodiment of capturing theimages of the region 314 includes a plurality of image sensors 304 a,304 b and a plurality of respective light sources 302 a, 302 b. Elementsof FIG. 7 that are analogous to elements in FIGS. 1-4 have been shown byindexing the reference numerals by 200. In this embodiment, the document316 may move in the direction indicated by the arrow 360 to pass in thelines of sight of each respective set of image sensors 304 a, 304 b andlight sources 302 a, 302 b. When the document 316 passes before theimage sensor 304 a and light source 302 a, the light source 302 a mayilluminate at least a portion of the region 314 with a first wavelengthof electromagnetic radiation while the image sensor 304 a captures afirst image of the region 314. The document 316 may then move in thelines of sight of the image sensor 304 b and the light source 302 b, atwhich point the light source 302 b may emit a second wavelength ofelectromagnetic radiation at the region 314 so that an image may becaptured of the region 314 at the second wavelength by the image sensor304 b. This process may continue in a similar manner for any number ofsets of image sensors and light sources so that any number of images maybe captured in this way. While the image sensors 304 a, 304 b are shownperpendicular to the surface of the document 316, it will he appreciatedthat each image sensor(s) may be at any suitable angle relative to thedocument surface and/or light source(s) 302 a, 302 b and remain withinthe scope of the present disclosure.

Referring to FIG. 8, an illustrative embodiment of a process forauthenticating a feature of the document, which may be implemented by adocument authentication application such as the document authenticationapplication 108 in FIG. 2, includes capturing a first image of theregion of a document while the region is subjected to a first wavelengthof electromagnetic radiation (step 401). The region may include at leasta portion of the document. The process may include determining a firstintensity value associated with the first image of the region (step403). In one example, the first intensity value may be a mean intensityvalue of the first image.

The process may also include comparing the first intensity value with afirst training intensity value of a region of a training document (step405). The first training intensity value may be obtained using the firstwavelength of electromagnetic radiation. The comparison may employ anysuitable means for comparing the measured data to training data.Non-limiting illustrative examples of comparative operations that may beemployed include difference, weighted difference, correlation todetermine a degree of similarity (or difference) between a measuredspectral profile and a training spectral profile, statisticaldifference, threshold test(s), or any other suitable computation.

The process may also include determining whether the document isauthentic based on the comparison between the first intensity value andthe first training intensity value (step 407). If the process determinesthat the document is not authentic based on the comparison between thefirst intensity value and the first training intensity value, theprocess determines that the document is not authentic (step 411). If theprocess determines that the document is authentic based on thecomparison between the first intensity value and the first trainingintensity value, the document is determined to be authentic (step 409).

Referring to FIG. 9, an illustrative embodiment of a process forauthenticating a feature of a document, which may be implemented by adocument authentication application such as the document authenticationapplication 108 in FIG. 2, includes capturing a plurality of images of aregion of the document (step 501). Each of the plurality of images iscaptured using one of a plurality of wavelengths of electromagneticradiation. The process may then determine a respective intensity valuefor each of the plurality of images (step 503). The process thencompares each of the respective intensity values with one of a pluralityof training intensity values of the region of the training document(step 505). Each of the plurality of training intensity values may beobtained using one of the plurality of wavelengths of electromagneticradiation. Each pair of respective intensity value and trainingintensity value that are compared to one another is obtained usingsubstantially the same wavelength. The comparison may employ anysuitable means for comparing the measured data to training data.Non-limiting illustrative examples of comparative operations that may beemployed include difference, weighted difference, correlation todetermine a degree of similarity (or difference) between a measuredspectral profile and a training spectral profile, statisticaldifference, threshold test(s), or any other suitable computation.

The process determines whether the document is authentic based on thecomparison between the respective intensity values and the plurality oftraining intensity values (step 507). If the process determines that thedocument is authentic based on the comparison between the respectiveintensity values and the plurality of training intensity values, thenthe document is determined to be authentic (step 509). If the processdetermines document is not authentic based on the comparison between therespective intensity values and the plurality of training intensityvalues, then the document is determined to not be authentic (step 511).

Referring to FIG. 10, an illustrative embodiment of a process forimplementing steps 503 and 505 in FIG. 9 includes selecting a portion ofthe pixels of at least one of the plurality of images for use indetermining the respective intensity value for the at least one of theplurality of images (step 601). The process includes determining arespective mean intensity value for each of the plurality of images(step 603). The process also includes normalizing the respective meanintensity values of the plurality of images (step 605). The process alsodetermines, for each of the plurality of images, a number of standarddeviations the mean intensity value differs from a correspondingtraining mean intensity value to determine whether the document isauthentic (step 607).

Referring to FIG. 11, an illustrative embodiment of a process forauthenticating a feature of a document, which may be implemented by adocument authentication application such as the document authenticationapplication 108 in FIG. 2, includes determining a spectral profile of aregion of a document in i predetermined electromagnetic radiation rangeusing two or more images of the region (step 701). Each of the two ormore images may be captured while the region is subjected to one of aplurality of wavelengths of electromagnetic radiation in thepredetermined electromagnetic range. The process also includes comparingthe spectral profile of the region of the document to a trainingspectral profile of a region of a training document (step 703). Thecomparison may employ any suitable means for comparing the measured datato training data. Non-limiting illustrative examples of comparativeoperations that may be employed include difference, weighted difference,correlation to determine a degree of similarity (or difference) betweena measured spectral profile and a training spectral profile, statisticaldifference, threshold, test(s), or any other suitable computation. Theprocess also includes determining whether the document is authenticbased on the comparison between the spectral profile and the trainingspectral profile (step 705).

The flowcharts and block diagrams in the different depicted embodimentsillustrate the architecture, functionality, and operation of somepossible implementations of apparatus, methods and computer programproducts. In this regard, each block in the flowchart or block diagramsmay represent a module, segment, or portion of code, which comprises oneor more executable instructions for implementing the specified functionor functions. In some alternative implementations, the function orfunctions noted in the block may occur out of the order noted in theFigures. For example, in some cases, two blocks shown in succession maybe executed substantially concurrently, or the blocks may sometimes beexecuted in the reverse order, depending upon the functionalityinvolved.

Referring to FIG. 12, a block diagram of a computing device 802 is shownin which the illustrative embodiments may be implemented. In oneembodiment, the document authentication application 108 described inFIG. 2 may be implemented on the computing device 802. Computer-usableprogram code or instructions implementing the processes used in theillustrative embodiments may be located on the computing device 802. Thecomputing device 802 includes a communications fabric 803, whichprovides communications between a processor unit 805, a memory 807, apersistent storage 809, a communications unit 811, an input/output (I/O)unit 813, and a display 815.

The processor unit 805 serves to execute instructions for software thatmay be loaded into the memory 807. The processor unit 805 may be a setof one or more processors or may be a multi-processor core, depending onthe particular implementation. Further, the processor unit 805 may beimplemented using one or more heterogeneous processor systems in which amain processor is present with secondary processors on a single chip. Asanother illustrative example, the processor unit 805 may be a symmetricmulti-processor system containing multiple processors of the same type.

The memory 807, in these examples, may be, for example, a random accessmemory or any other suitable volatile or non-volatile storage device.The persistent storage 809 may take various forms depending on theparticular implementation. For example, the persistent storage 809 maycontain one or more components or devices. For example, the persistentstorage 809 may be a hard drive, a flash memory, a rewritable opticaldisk, a rewritable magnetic tape, or some combination of the above. Themedia used by the persistent storage 809 also may be removable. Forexample, a removable hard drive may be used for the persistent storage809.

The communications unit 811, in these examples, provides forcommunications with other data processing systems or communicationdevices. In these examples, the communications unit 811 may be a networkinterface card. The communications unit 811 may provide communicationsthrough the use of either or both physical and wireless communicationlinks.

The input/output unit 813 allows for the input and output of data withother devices that may be connected to the computing device 802. Forexample, the input/output unit 813 may provide a connection for userinput through a keyboard and mouse. Further, the input/output, unit 813may send output to a processing device. In the case in which thecomputing device 802 is a cellular phone, the input/output unit 813 mayalso allow devices to be connected to the cellular phone, such asmicrophones, headsets, and controllers. The display 815 provides amechanism to display information to a user, such as a graphical userinterface.

Instructions for the operating system and applications or programs arelocated on the persistent storage 809. These instructions may be loadedinto the memory 807 for execution by the processor unit 805. Theprocesses of the different embodiments may be performed by the processorunit 805 using computer-implemented instructions, which may be locatedin a memory, such as the memory 807. These instructions are referred toas program code, computer-usable program code, or computer-readableprogram code that may be read and executed by a processor in theprocessor unit 805. The program code in the different embodiments may beembodied on different physical or tangible computer-readable media, suchas the memory 807 or the persistent storage 809.

Program code 817 is located in a functional form on a computer-readablemedia 819 and may be loaded onto or transferred to the computing device802 for execution by the processor unit 805. The program code 817 andthe computer-readable media 819 form computer program product 821 inthese examples. In one embodiment, the computer program product 821 isthe document authentication application 108 described in FIG. 2. In thisembodiment, the program code 817 may include computer-usable programcode capable of capturing a first image of a region of a document whilethe region is subjected to a first wavelength of electromagneticradiation. The region includes at least a portion of the document. Theprogram code 817 may also include computer-usable program code capableof determining a first intensity value associated with the first imageof the region, and comparing the first intensity value with a firsttraining intensity value of a region of a training document. The firsttraining intensity value is obtained using the first wavelength ofelectromagnetic radiation. The program code 817 may also includecomputer-usable program code capable of determining whether the documentis authentic at least partially based on the comparison between thefirst intensity value and the first training intensity value.

In another embodiment, the program code 817 may include computer-usableprogram code capable of determining spectral profile of a region of adocument in a predetermined electromagnetic radiation range using two ormore images of the region. The region includes at least a portion of thedocument. Each of the two or more images is captured while the region issubjected to one of a plurality of wavelengths of electromagneticradiation in the predetermined electromagnetic radiation range. Theprogram code 817 may also include computer-usable program code capableof comparing the spectral profile of the region of the document to atraining spectral profile of a region of a training document, anddetermining whether the document is authentic based on the comparisonbetween the spectral profile and the training spectral profile. Anycombination of the above-mentioned computer-usable program code may beimplemented in the program code 817, and any functions of theillustrative embodiments may be implemented in the program code 817.

In one example, the computer-readable media 819 may be in a tangibleform, such as, for example, an optical or magnetic disc that is insertedor placed into a drive or other device that is part of the persistentstorage 809 for transfer onto a storage device, such as a hard drivethat is part of the persistent storage 809. In a tangible form, thecomputer-readable media 819 also may take the form of a persistentstorage, such as a hard drive or a flash memory that is connected to thecomputing device 802. The tangible form of the computer-readable media319 is also referred to as computer recordable storage media.

Alternatively, the program code 817 may be transferred to the computingdevice 802 from the computer readable media 819 through a communicationlink to the communications unit 811 or through a connection theinput/output unit 313. The communication link or the connection may bephysical or wireless in the illustrative examples. The computer-readablemedia 819 also may take the form of non-tangible media, such ascommunication links or wireless transmissions containing the programcode 817. In one embodiment, the program code 817 is delivered to thecomputing device 802 over the Internet.

The different components illustrated for the computing device 802 arenot meant to provide architectural limitations to the manner in whichdifferent embodiments may be implemented. The different illustrativeembodiments may be implemented in a data processing system includingcomponents in addition to or in place of those illustrated for computingdevice 802. Other components shown in FIG. 12 can be varied from theillustrative examples shown.

As one example, a storage device in the computing device 802 is anyhardware apparatus that may store data. The memory 807, the persistentstorage 809, and the computer-readable media 819 are examples of storagedevices in a tangible form.

In another example, a bus system may be used to implement thecommunications fabric 803 and may be comprised of one or more buses,such as a system bus or an input/output bus. Of course, the bus systemmay be implemented using any suitable type of architecture that providesfor a transfer of data between different components or devices attachedto the bus system. Additionally, the communications unit 811 may includeone or more devices used to transmit and receive data, such as a modemor a network adapter. Further, a memory may be, for example, the memory807 or a cache such as found in an interface and memory controller hubthat may be present in the communications fabric 803.

As used herein, including in the claims, the terms first, second, third,etc. . . . used in relation to an element (e.g., first wavelength,second wavelength, etc.) are for reference or identification purposesonly, and these terms, unless otherwise indicated, are not intended todescribe or suggest a number, order, source, purpose, or substantivequality for any element for which such a term is used.

Although the illustrative embodiments described herein have beendisclosed in the context of certain illustrative, non-limitingembodiments, it should be understood that various changes,substitutions, permutations, and alterations can be made withoutdeparting from the scope of the invention as defined by the appendedclaims. It will be appreciated that any feature that is described in aconnection to any one embodiment may also be applicable to any otherembodiment.

What is claimed is:
 1. A method for authenticating a feature of adocument, the method comprising: providing a document authenticationsystem comprising: at least one electromagnetic radiation emitter forselectively illuminating the document with at least two frequencies ofelectromagnetic ration, at least one image sensor for capturing imagesof the document when subjected to electromagnetic radiation from the atleast one electromagnetic radiation emitter, and a computing device forcontrolling the at least one electromagnetic radiation emitter and theat least one image sensor, wherein the computing device includes adocument authentication application having a image capturing module, atraining module, an image analysis module, and a comparison module;subjecting a region of the document to different first and secondwavelengths of electromagnetic radiation emitted from the at least oneelectromagnetic radiation emitter and capturing with the at least oneimage sensor a first image and a second image of the region of thedocument corresponding to the first and second wavelengths ofelectromagnetic radiation, respectively, the region comprising at leasta portion of the document; determining a first intensity valueassociated with the first image of the region and determining a secondintensity value associated with the second image of the region; usingthe comparison module to compare the first intensity value with a firsttraining intensity value of a region of a training document, the firsttraining intensity value obtained using the first wavelength ofelectromagnetic radiation, and comparing the second intensity value witha second training intensity value of the region of the trainingdocument, the second training intensity value obtained using the secondwavelength of electromagnetic radiation; and determining whether thedocument is authentic at least partially based on the comparison betweenthe first intensity value and the first training intensity value andusing the comparison between the second intensity value and the secondtraining intensity value.
 2. A method for authenticating a feature of adocument, the method comprising: capturing with an image sensor a firstimage of a region of a document while the region is subjected to a firstwavelength of electromagnetic radiation emitted from a electromagneticradiation emitter, the region comprising at least a portion of thedocument; providing the first image to a computing device including aprocessing unit; wherein the computing device is configured to performsteps comprising: determining a first intensity value associated withthe first image of the region, comparing the first intensity value witha first training intensity value of a region of a training documentusing a comparison module, the first training intensity value obtainedusing the first wavelength of electromagnetic radiation, and determiningwhether the document is authentic at least partially based on thecomparison between the first intensity value and the first trainingintensity value; wherein capturing the first image of the region of thedocument while the region is subjected to the first wavelength ofelectromagnetic radiation comprises capturing a plurality of images ofthe region of the document, each of the plurality of images capturedusing one of a plurality of wavelengths of electromagnetic radiation;wherein determining the first intensity value associated with the firstimage of the region comprises determining a respective intensity valuefor each of the plurality of images; wherein comparing the firstintensity value with the first training intensity value comprisescomparing each of the respective intensity values with one of aplurality of training intensity values of the region of the trainingdocument, each of the plurality of training intensity values obtainedusing one of the plurality of wavelengths of electromagnetic radiation,wherein each pair of respective intensity values and training intensityvalues that are compared to one another are obtained using substantiallythe same wavelength; and wherein determining whether the document isauthentic comprises determining whether the document is authentic atleast partially based on the comparison between the respective intensityvalues and the plurality of training intensity values.
 3. The method ofclaim 2, further comprising: normalizing the respective intensity valuesof the plurality of images prior to comparing each of the respectiveintensity values with one of the plurality of training intensity values.4. The method of claim 3, wherein normalizing the respective intensityvalues of the plurality of images comprises dividing each of therespective intensity values by a selected one of the respectiveintensity values.
 5. The method of claim 2, wherein each of therespective intensity values comprises a mean intensity value; whereineach of the plurality of training intensity values comprises a trainingmean intensity value and a training standard deviation; whereincomparing each of the respective intensity values with one of theplurality of training intensity values comprises determining, for eachof the plurality of images, a number of training standard deviations themean intensity value differs from the corresponding training meanintensity value; and wherein determining whether the document isauthentic at least partially based on the comparison between therespective intensity values and the plurality of training intensityvalues comprises determining an average deviation between the meanintensity values and the training mean intensity values and determiningwhether the average deviation meets or exceeds a predeterminedthreshold.
 6. The method of claim 2, wherein each of the respectiveintensity values comprises a mean intensity value; wherein each of theplurality of training intensity values comprises a training meanintensity value and a training standard deviation; wherein comparingeach of the respective intensity values with one of the plurality oftraining intensity values comprises determining, for each of theplurality of images, a number of training standard deviations the meanintensity value differs from the corresponding training mean intensityvalue; and wherein determining whether the document is authentic atleast partially based on the comparison between the respective intensityvalues and the plurality of training intensity values comprisesdetermining a largest deviation between one of the mean intensity valuesand a corresponding one of the plurality of training mean intensityvalues and determining whether the largest deviation, meets or exceeds apredetermined threshold.
 7. The method of claim 2, wherein capturing theplurality of images of the region of the document comprises: capturing aplurality of line images of the region, each of the plurality of linesimages captured while one of the plurality of wavelengths ofelectromagnetic radiation at least partially illuminates the region,wherein each set of line images in the plurality of line it capturedusing a common wavelength of electromagnetic radiation are used to formone of the images in the plurality of images.
 8. The method of claim 2,further comprising: selecting a portion of the pixels of at least one ofthe plurality of images for use in determining the respective intensityvalue for the at least one of the plurality of images.
 9. The method ofclaim 8, further comprising: generating a histogram for the at least oneof the plurality of images, the histogram comprising pixel intensitydata versus percentage of pixels for the at least one of the pluralityof images; wherein the portion of the pixels of the at least one of theplurality of images used to determine the respective intensity value forthe at least one of the plurality of images is selected using thehistogram.
 10. The method of claim 9, wherein a respective histogram isgenerated for each of the plurality of images; and wherein the portionof the pixels of each of plurality of images used to determine therespective intensity value for each of the plurality of images isselected using the respective histograms.
 11. The method of claim 9,wherein the first intensity value comprises a first mean intensityvalue; wherein the first training intensity value comprises a trainingmean intensity value and a training standard deviation; and whereincomparing the first intensity value with the first training intensityvalue of the region of the training document comprises determining anumber of training standard deviations that the first mean intensityvalue differs from the training mean intensity value.
 12. The method ofclaim 11, wherein determining whether the document is authentic at leastpartially based on the comparison between the first intensity value andthe first training intensity value comprises determining whether thefirst mean intensity value differs from the training mean intensityvalue by a predetermined threshold number of training standarddeviations.
 13. A method for authenticating a feature of a document, themethod comprising providing at least one image sensor, at least oneelectromagnetic radiation emitter, and a computing device having aprocessor configured to implement a computer-implemented methodcomprising: determining a spectral profile of a region of a document ina predetermined electromagnetic radiation range using two or more imagesof the region, the region comprising at least a portion of the document,each of the two or more images captured with the at least one imagesensor while the region is subjected to at least two differentwavelengths of a plurality of wavelengths of electromagnetic radiationemitted from the at least one electromagnetic radiation emitter in thepredetermined electromagnetic radiation range corresponding to the twoor more captured images; comparing the spectral profile of the region ofthe document to a training spectral profile of a region of a trainingdocument; and determining whether the document is authentic based on thecomparison between the spectral profile and the training spectralprofile.
 14. The method of claim 13, wherein the spectral profile of theregion comprises an intensity value of each of the two or more images ofthe region.
 15. The method of claim 13, prior to determining thespectral profile of the region of the document, determining the trainingspectral profile of the region of the training document.
 16. The methodof claim 13, wherein each of the two or more images are captured whilethe region is subjected to a different one of the plurality ofwavelengths of electromagnetic radiation.